<scp>MAFLD</scp> fibrosis score: Using routine measures to identify advanced fibrosis in metabolic‐associated fatty liver disease
Johnny T. K. Cheung, Xinrong Zhang, Grace Lai‐Hung Wong, Terry Cheuk‐Fung Yip, Huapeng Lin, Guanlin Li, Howard H.W. Leung, Jimmy Che‐To Lai, Sanjiv Mahadeva, Nik Raihan Nik Mustapha, Xiaodong Wang, Wen‐Yue Liu, Vincent Wai‐Sun Wong, Wah‐Kheong Chan, Ming‐Hua Zheng
Abstract
BACKGROUND: Early screening may prevent fibrosis progression in metabolic-associated fatty liver disease (MAFLD). AIMS: We developed and validated MAFLD fibrosis score (MFS) for identifying advanced fibrosis (≥F3) among MAFLD patients. METHODS: This cross-sectional, multicentre study consecutively recruited MAFLD patients receiving tertiary care (Malaysia as training cohort [n = 276] and Hong Kong and Wenzhou as validation cohort [n = 431]). Patients completed liver biopsy, vibration-controlled transient elastography (VCTE), and clinical and laboratory assessment within 1 week. We used machine learning to select 'highly important' predictors of advanced fibrosis, followed by backward stepwise regression to construct MFS formula. RESULTS: MFS was composed of seven variables: age, body mass index, international normalised ratio, aspartate aminotransferase, gamma-glutamyl transpeptidase, platelet count, and history of type 2 diabetes. MFS demonstrated an area under the receiver-operating characteristic curve of 0.848 [95% CI 0.800-898] and 0.823 [0.760-0.886] in training and validation cohorts, significantly higher than aminotransferase-to-platelet ratio index (0.684 [0.603-0.765], 0.663 [0.588-0.738]), Fibrosis-4 index (0.793 [0.735-0.854], 0.737 [0.660-0.814]), and non-alcoholic fatty liver disease fibrosis score (0.785 [0.731-0.844], 0.750 [0.674-0.827]) (DeLong's test p < 0.05). MFS could include 92.3% of patients using dual cut-offs of 14 and 15, with a correct prediction rate of 90.4%, resulting in a larger number of patients with correct diagnosis compared to other scores. A two-step MFS-VCTE screening algorithm demonstrated positive and negative predictive values and overall diagnostic accuracy of 93.4%, 89.5%, and 93.2%, respectively, with only 4.0% of patients classified into grey zone. CONCLUSION: MFS outperforms conventional non-invasive scores in predicting advanced fibrosis, contributing to screening in MAFLD patients.